Free toolsPrompt & token estimator
Prompt & token length estimator for learning content
Plan AI-assisted lessons and tutoring: see rough token size, word count, and how much of a typical model context window your prompt might use—before you paste into a chat or API.
Estimated tokens
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Words
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Characters
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UTF-8 bytes
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Why length matters for educational prompts
Models pay attention across the whole context you send. Stuffing in an entire course worth of text in one prompt leaves less room for the learner’s questions, your rubric, and the model’s answer. A quick length check helps you trim boilerplate, move long readings to attachments, or split work across sessions—especially when you are comparing providers or context sizes.
When you are ready to go from a measured prompt to a full course generated for learners, Ailurn builds structured lessons from your goals so you are not manually filling context windows line by line.
Frequently asked questions
- Why not an exact token count?
- Exact counts need the same tokenizer your provider uses (model- and version-specific). This tool uses common rules of thumb so you can plan lesson prompts and tutoring threads without installing SDKs—expect ±10–20% variance.
- Which heuristic should I use?
- For English prose and mixed text, “~4 characters per token” is widely cited. The “~1.3 tokens per word” option is a second check; they may disagree for code, lists, or non-Latin scripts.
- How does this help teaching or course design?
- Large prompts (full readings, long rubrics, and chat history) eat context quickly. Estimating length helps you decide what to put in the system prompt, what to attach as files, and when to start a fresh thread for a new module.
- Is my text uploaded?
- No. Estimates run entirely in your browser.
- Does this include tool calls or images?
- No. Only the text you paste is measured. Images, PDFs, and tool outputs would add tokens in real use—leave headroom.